Clinical utility of genome sequencing in autism: illustrative examples from a genomic research study
Bibliographic record
Abstract
BACKGROUND: Genetics is an important contributor to autism spectrum disorder (ASD). Clinical guidelines endorse genetic testing in the medical workup of ASD, particularly tests that use whole genome sequencing (WGS) technology. While the clinical utility of genetic testing in ASD is demonstrated, the breadth of impact of results can depend on the variant and/or gene being reported. METHODS: We reviewed research results returned to families enrolled in our ASD WGS study between 2012 and 2023. For significant results, we grouped the outcome of each genetic finding into three outcome categories: (1) genetic diagnosis, (2) counselling benefits and (3) support to family. RESULTS: Out of 202 families who received genome sequencing results, 100 had at least one clinically relevant finding related to ASD. With detailed examples, we show that all significant results led to a genetic diagnosis and counselling benefits. CONCLUSION: Our findings show the relevance of genome sequencing in ASD and provide illustrative examples of how the information can be used.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".